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ORCIDInioluwa Deborah Raji
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- affiliation: Mozilla Foundation, USA
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2020 – today
- 2025
[c21]Inioluwa Deborah Raji, Lydia T. Liu:
Evaluating Prediction-based Interventions with Human Decision Makers In Mind. AISTATS 2025: 1180-1188- [c20]Victor Ojewale
, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji:
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. CHI 2025: 815:1-815:29 - [c19]Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean, Inioluwa Deborah Raji, Travis Zack:
Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity. ICML (Position Papers) 2025 - [c18]Jessica Dai, Paula Gradu, Inioluwa Deborah Raji, Benjamin Recht:
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms. ICML 2025 - [i29]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng:
International AI Safety Report. CoRR abs/2501.17805 (2025) - [i28]Jessica Dai, Paula Gradu, Inioluwa Deborah Raji, Benjamin Recht:
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms. CoRR abs/2502.08166 (2025) - [i27]Laura Weidinger, Inioluwa Deborah Raji, Hanna M. Wallach, Margaret Mitchell, Angelina Wang, Olawale Salaudeen, Rishi Bommasani, Deep Ganguli, Sanmi Koyejo, William Isaac:
Toward an Evaluation Science for Generative AI Systems. CoRR abs/2503.05336 (2025) - [i26]Inioluwa Deborah Raji, Lydia T. Liu:
Evaluating Prediction-based Interventions with Human Decision Makers In Mind. CoRR abs/2503.05704 (2025) - [i25]Ahmed M. Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean, Inioluwa Deborah Raji, Travis Zack:
Medical Large Language Model Benchmarks Should Prioritize Construct Validity. CoRR abs/2503.10694 (2025) - [i24]Rishi Bommasani, Scott R. Singer, Ruth E. Appel, Sarah H. Cen, A. Feder Cooper, Elena Cryst, Lindsey A. Gailmard, Ian Klaus, Meredith M. Lee, Inioluwa Deborah Raji, Anka Reuel, Drew Spence, Alexander Wan, Angelina Wang, Daniel Zhang, Daniel E. Ho, Percy Liang, Dawn Song, Joseph E. Gonzalez, Jonathan Zittrain, Jennifer Tour Chayes, Mariano-Florentino Cuellar, Li Fei-Fei:
The California Report on Frontier AI Policy. CoRR abs/2506.17303 (2025) - [i23]Jessica Dai, Inioluwa Deborah Raji, Benjamin Recht, Irene Y. Chen:
Aggregated Individual Reporting for Post-Deployment Evaluation. CoRR abs/2506.18133 (2025) - [i22]Victor Ojewale, Inioluwa Deborah Raji, Suresh Venkatasubramanian:
Multi-lingual Functional Evaluation for Large Language Models. CoRR abs/2506.20793 (2025) - [i21]Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson:
Bridging Prediction and Intervention Problems in Social Systems. CoRR abs/2507.05216 (2025) - [i20]Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou, Franziska Sofia Hafner, Harry Mayne, Jan Batzner, Negar Foroutan, Chris Schmitz, Karolina Korgul, Hunar Batra, Oishi Deb, Emma Beharry, Cornelius Emde, Thomas Foster, Anna Gausen, María Grandury, Simeng Han, Valentin Hofmann, Lujain Ibrahim, Hazel Kim, Hannah Rose Kirk, Fangru Lin, Gabrielle Kaili-May Liu, Lennart Luettgau, Jabez Magomere, Jonathan Rystrøm, Anna Sotnikova, Yushi Yang, Yilun Zhao, Adel Bibi, Antoine Bosselut, Ronald Clark, Arman Cohan, Jakob N. Foerster, Yarin Gal, Scott A. Hale, Inioluwa Deborah Raji, Christopher Summerfield, Philip H. S. Torr, Cozmin Ududec, Luc Rocher, Adam Mahdi:
Measuring what Matters: Construct Validity in Large Language Model Benchmarks. CoRR abs/2511.04703 (2025) - 2024
- [c17]Hellina Hailu Nigatu, Inioluwa Deborah Raji:
"I Searched for a Religious Song in Amharic and Got Sexual Content Instead'': Investigating Online Harm in Low-Resourced Languages on YouTube. FAccT 2024: 141-160 - [c16]Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen:
The Data Addition Dilemma. MLHC 2024 - [c15]Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji:
AI auditing: The Broken Bus on the Road to AI Accountability. SaTML 2024: 612-643 - [i19]Inioluwa Deborah Raji, Roel Dobbe:
Concrete Problems in AI Safety, Revisited. CoRR abs/2401.10899 (2024) - [i18]Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji:
AI auditing: The Broken Bus on the Road to AI Accountability. CoRR abs/2401.14462 (2024) - [i17]Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane, Inioluwa Deborah Raji:
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. CoRR abs/2402.17861 (2024) - [i16]Hellina Hailu Nigatu, Inioluwa Deborah Raji:
"I Searched for a Religious Song in Amharic and Got Sexual Content Instead": Investigating Online Harm in Low-Resourced Languages on YouTube. CoRR abs/2405.16656 (2024) - [i15]Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen:
The Data Addition Dilemma. CoRR abs/2408.04154 (2024) - [i14]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Danielle Goldfarb, Hoda Heidari, Leila Khalatbari, Shayne Longpre, Vasilios Mavroudis, Mantas Mazeika, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Theodora Skeadas, Florian Tramèr, Bayo Adekanmbi, Paul F. Christiano, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Nick R. Jennings, Andreas Krause, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Arvind Narayanan, Alondra Nelson, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang:
International Scientific Report on the Safety of Advanced AI (Interim Report). CoRR abs/2412.05282 (2024) - 2023
- [j4]Inioluwa Deborah Raji, Joy Buolamwini:
Actionable Auditing Revisited: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. Commun. ACM 66(1): 101-108 (2023) - [c14]Daricia Wilkinson, Kate Crawford, Hanna M. Wallach, Inioluwa Deborah Raji, Bogdana Rakova, Ranjit Singh, Angelika Strohmayer, Ethan Zuckerman:
Accountability in Algorithmic Systems: From Principles to Practice. CHI Extended Abstracts 2023: 521:1-521:4 - [c13]Jee Young Kim, William Boag, Freya Gulamali, Alifia Hasan, Henry David Jeffry Hogg, Mark Lifson, Deirdre K. Mulligan, Manesh Patel, Inioluwa Deborah Raji, Ajai Sehgal, Keo Shaw, Danny Tobey, Alexandra Valladares, David E. Vidal, Suresh Balu, Mark P. Sendak:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. FAccT 2023: 1396-1417 - [i13]Jee Young Kim, William Boag, Freya Gulamali, Alifia Hasan, Henry David Jeffry Hogg, Mark Lifson, Deirdre K. Mulligan, Manesh Patel, Inioluwa Deborah Raji, Ajai Sehgal, Keo Shaw, Danny Tobey, Alexandra Valladares, David E. Vidal, Suresh Balu, Mark P. Sendak:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. CoRR abs/2304.13081 (2023) - [i12]Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - [i11]Sasha Costanza-Chock, Emma Harvey, Inioluwa Deborah Raji, Martha Czernuszenko, Joy Buolamwini:
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. CoRR abs/2310.02521 (2023) - 2022
- [c12]Inioluwa Deborah Raji:
From Algorithmic Audits to Actual Accountability: Overcoming Practical Roadblocks on the Path to Meaningful Audit Interventions for AI Governance. AIES 2022: 5 - [c11]Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho:
Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. AIES 2022: 557-571 - [c10]Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst:
The Fallacy of AI Functionality. FAccT 2022: 959-972 - [c9]Sasha Costanza-Chock, Inioluwa Deborah Raji, Joy Buolamwini:
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. FAccT 2022: 1571-1583 - [c8]Carolyn Ashurst, Solon Barocas, Rosie Campbell, Inioluwa Deborah Raji:
Disentangling the Components of Ethical Research in Machine Learning. FAccT 2022: 2057-2068 - [i10]Inioluwa Deborah Raji, Peggy Xu, Colleen Honigsberg, Daniel E. Ho:
Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. CoRR abs/2206.04737 (2022) - [i9]Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz, Andrew D. Selbst:
The Fallacy of AI Functionality. CoRR abs/2206.09511 (2022) - 2021
- [j3]Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, Alex Hanna:
Data and its (dis)contents: A survey of dataset development and use in machine learning research. Patterns 2(11): 100336 (2021) - [c7]Inioluwa Deborah Raji, Morgan Klaus Scheuerman, Razvan Amironesei:
You Can't Sit With Us: Exclusionary Pedagogy in AI Ethics Education. FAccT 2021: 515-525 - [c6]Thomas Liao, Rohan Taori, Inioluwa Deborah Raji, Ludwig Schmidt:
Are We Learning Yet? A Meta Review of Evaluation Failures Across Machine Learning. NeurIPS Datasets and Benchmarks 2021 - [c5]Inioluwa Deborah Raji, Emily Denton, Emily M. Bender, Alex Hanna, Amandalynne Paullada:
AI and the Everything in the Whole Wide World Benchmark. NeurIPS Datasets and Benchmarks 2021 - [i8]Inioluwa Deborah Raji, Genevieve Fried:
About Face: A Survey of Facial Recognition Evaluation. CoRR abs/2102.00813 (2021) - [i7]Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton, Alex Hanna:
AI and the Everything in the Whole Wide World Benchmark. CoRR abs/2111.15366 (2021) - 2020
- [j2]Inioluwa Deborah Raji:
The Discomfort of Death Counts: Mourning through the Distorted Lens of Reported COVID-19 Death Data. Patterns 1(4): 100066 (2020) - [j1]Inioluwa Deborah Raji:
Handle with Care: Lessons for Data Science from Black Female Scholars. Patterns 1(8): 100150 (2020) - [c4]Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton:
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. AIES 2020: 145-151 - [c3]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing. FAT* 2020: 33-44 - [i6]Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton:
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing. CoRR abs/2001.00964 (2020) - [i5]Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes:
Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. CoRR abs/2001.00973 (2020) - [i4]Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, Alex Hanna:
Data and its (dis)contents: A survey of dataset development and use in machine learning research. CoRR abs/2012.05345 (2020)
2010 – 2019
- 2019
- [c2]Inioluwa Deborah Raji, Joy Buolamwini:
Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. AIES 2019: 429-435 - [c1]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. FAT 2019: 220-229 - [i3]Alice Xiang, Inioluwa Deborah Raji:
On the Legal Compatibility of Fairness Definitions. CoRR abs/1912.00761 (2019) - [i2]Inioluwa Deborah Raji, Jingying Yang:
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles. CoRR abs/1912.06166 (2019) - 2018
- [i1]Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru:
Model Cards for Model Reporting. CoRR abs/1810.03993 (2018)
Coauthor Index
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